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Gene expression studies in prostate cancer tissue: which reference gene should be selected for normalization?

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Abstract

Using quantitative reverse transcription–polymerase chain reaction (RT-PCR), reference genes are utilized as endogenous controls for relative quantification of target genes in gene profiling studies. The suitability of housekeeping genes for that purpose in prostate cancer tissue has not been sufficiently investigated so far. The objective of this study was to select from a panel of 16 potential candidate reference genes the most stable genes for gene normalization. Expression of mRNA encoding ACTB, ALAS1, ALB, B2M, G6PD, GAPD, HMBS, HPRT1, K-ALPHA-1, POLR2A, PPIA, RPL13A, SDHA, TBP, UBC, and YWHAZ was examined in matched, microdissected malignant and nonmalignant tissue specimens obtained from 17 nontreated prostate carcinomas after radical prostatectomy by real-time RT-PCR. The genes studied displayed a wide expression range with cycle threshold values between 16 and 37. The expression was not different between samples from pT2 and pT3 tumors or between samples with Gleason scores <7 and ≥7 (P>0.05). ACTB, RPL13A, and HMBS showed significant differences (P<0.02 at least) in expressions between malignant and nonmalignant pairs. All other genes did not differ between the matched pairs, and the software programs geNorm and NormFinder were used to ascertain the most suitable reference genes from these candidates. HPRT1, ALAS1, and K-ALPHA-1 were calculated by both programs to be the most stable genes covering a broad range of expression. The expression of the target gene RECK normalized with HRPT1 alone and with the normalization factors generated by the combination of these three reference genes as well as with the unstable genes ACTB or RPL13A is given. That example shows the significance of using suitable reference genes to avoid erroneous normalizations in gene profiling studies for prostate cancer. The use of HPRT1 alone as a reference gene shown in our study was sufficient, but the normalization factors generated from two (HRPT1, ALAS1) or all three genes (HRPT1, ALAS1, K-ALPHA-1) should be considered for an improved reliability of normalization in gene profiling studies of prostate cancer.

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References

  1. Karge WH, III, Schaefer EJ, Ordovas JM (1998) Quantification of mRNA by polymerase chain reaction (PCR) using an internal standard and a nonradioactive detection method. Methods Mol Biol 110:43–61

    PubMed  Google Scholar 

  2. Bustin SA (2000) Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. J Mol Endocrinol 25:169–193

    Article  PubMed  Google Scholar 

  3. Suzuki T, Higgins PJ, Crawford DR (2000) Control selection for RNA quantitation. Biotechniques 29:332–337

    PubMed  Google Scholar 

  4. Thellin O, Zorzi W, Lakaye B, De Borman BB, Coumans B, Hennen G, Grisar T, Igout A, Heinen E (1999) Housekeeping genes as internal standards: use and limits. J Biotechnol 75:291–295

    Article  PubMed  Google Scholar 

  5. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3:research0034.1–research0034.11

    Article  Google Scholar 

  6. Radonic A, Thulke S, Mackay IM, Landt O, Siegert W, Nitsche A (2004) Guideline to reference gene selection for quantitative real-time PCR. Biochem Biophys Res Commun 313:856–862

    Article  PubMed  Google Scholar 

  7. Tricarico C, Pinzani P, Bianchi S, Paglierani M, Distante V, Pazzagli M, Bustin SA, Orlando C (2002) Quantitative real-time reverse transcription polymerase chain reaction: normalization to rRNA or single housekeeping genes is inappropriate for human tissue biopsies. Anal Biochem 309:293–300

    Article  PubMed  Google Scholar 

  8. Dheda K, Huggett JF, Bustin SA, Johnson MA, Rook G, Zumla A (2004) Validation of housekeeping genes for normalizing RNA expression in real-time PCR. Biotechniques 37:112–119

    PubMed  Google Scholar 

  9. Schmittgen TD, Zakrajsek BA (2000) Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR. J Biochem Biophys Methods 46:69–81

    Article  PubMed  Google Scholar 

  10. Goidin D, Mamessier A, Staquet MJ, Schmitt D, Berthier-Vergnes O (2001) Ribosomal 18S RNA prevails over glyceraldehyde-3-phosphate dehydrogenase and beta-actin genes as internal standard for quantitative comparison of mRNA levels in invasive and noninvasive human melanoma cell subpopulations. Anal Biochem 295:17–21

    Article  PubMed  Google Scholar 

  11. Nagler DK, Kruger S, Kellner A, Ziomek E, Menard R, Buhtz P, Krams M, Roessner A, Kellner U (2004) Up-regulation of cathepsin X in prostate cancer and prostatic intraepithelial neoplasia. Prostate 60:109–119

    Article  PubMed  Google Scholar 

  12. Katenkamp K, Berndt A, Hindermann W, Wunderlich H, Haas KM, Borsi L, Zardi L, Kosmehl H (2004) mRNA expression and protein distribution of the unspliced tenascin-C isoform in prostatic adenocarcinoma. J Pathol 203:771–779

    Article  PubMed  Google Scholar 

  13. Jung C, Kim RS, Zhang HJ, Lee SJ, Jeng MH (2004) HOXB13 induces growth suppression of prostate cancer cells as a repressor of hormone-activated androgen receptor signaling. Cancer Res 64:9185–9192

    Article  PubMed  Google Scholar 

  14. Tian W, Osawa M, Horiuchi H, Tomita Y (2004) Expression of the prolactin-inducible protein (PIP/GCDFP15) gene in benign epithelium and adenocarcinoma of the prostate. Cancer Sci 95:491–495

    Article  PubMed  Google Scholar 

  15. Bustin SA (2002) Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): trends and problems. J Mol Endocrinol 29:23–39

    Article  PubMed  Google Scholar 

  16. Almeida A, Paul TJ, Magdelenat H, Radvanyi F (2004) Gene expression analysis by real-time reverse transcription polymerase chain reaction: influence of tissue handling. Anal Biochem 328:101–108

    Article  PubMed  Google Scholar 

  17. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2004) GeNorm software manual, update 6 Sep 2004. http://medgen.ugent.be/~jvdesomp/genorm

  18. Andersen CL, Jensen JL, Orntoft TF (2004) Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res 64:5245–5250

    Article  PubMed  Google Scholar 

  19. Sobin LH, Wittekind C (2002) TNM classification of malignant tumours, 6th edn. Wiley-Liss, New York, pp 184–187

    Google Scholar 

  20. Gleason DF (1988) Histologic grade, clinical stage, and patient age in prostate cancer. NCI Monogr 7:15–18

    PubMed  Google Scholar 

  21. Kristiansen G, Pilarsky C, Wissmann C, Stephan C, Weissbach L, Loy V, Loening S, Dietel M, Rosenthal A (2003) ALCAM/CD166 is up-regulated in low-grade prostate cancer and progressively lost in high-grade lesions. Prostate 54:34–43

    Article  PubMed  Google Scholar 

  22. Mueller O, Lightfoot S, Schroeder A (2004) RNA integrity number (RIN)—standardization of RNA quality control. Agilent Technologies, Palo Alto

    Google Scholar 

  23. Miller CL, Diglisic S, Leister F, Webster M, Yolken RH (2004) Evaluating RNA status for RT-PCR in extracts of postmortem human brain tissue. Biotechniques 36:628–633

    PubMed  Google Scholar 

  24. Rasmussen R (2001) Quantification on the LightCycler. In: Meuer S, Wittwer C, Nakagawara K (eds) Rapid cycle real-time PCR, methods and applications. Springer, Berlin Heidelberg New York, pp 21–34

    Google Scholar 

  25. de Kok JB, Roelofs RW, Giesendorf BA, Pennings JL, Waas ET, Feuth T, Swinkels DW, Span PN (2005) Normalization of gene expression measurements in tumor tissues: comparison of 13 endogenous control genes. Lab Invest 85:154–159

    PubMed  Google Scholar 

  26. Imbeaud S, Graudens E, Boulanger V, Barlet X, Zaborski P, Eveno E, Mueller O, Schroeder A, Auffray C (2005) Towards standardization of RNA quality assessment using user-independent classifiers of microcapillary electrophoresis traces. Nucleic Acids Res 33:e56

    Article  PubMed  Google Scholar 

  27. Schmid H, Cohen CD, Henger A, Irrgang S, Schlondorff D, Kretzler M (2003) Validation of endogenous controls for gene expression analysis in microdissected human renal biopsies. Kidney Int 64:356–360

    Article  PubMed  Google Scholar 

  28. Nelson PS (2004) Predicting prostate cancer behavior using transcript profiles. J Urol 172:S28–S32

    Article  PubMed  Google Scholar 

  29. Haller F, Kulle B, Schwager S, Gunawan B, von Heydebreck A, Sultmann H, Fuzesi L (2004) Equivalence test in quantitative reverse transcription polymerase chain reaction: confirmation of reference genes suitable for normalization. Anal Biochem 335:1–9

    Article  PubMed  Google Scholar 

  30. Szabo A, Perou CM, Karaca M, Perreard L, Quackenbush JF, Bernard PS (2004) Statistical modeling for selecting housekeeper genes. Genome Biol 5:R59

    Article  PubMed  Google Scholar 

  31. Janssens N, Janicot M, Perera T, Bakker A (2004) Housekeeping genes as internal standards in cancer research. Mol Diagn 8:107–113

    PubMed  Google Scholar 

  32. Kim S, Kim T (2003) Selection of optimal internal controls for gene expression profiling of liver disease. Biotechniques 35:456–458 (460)

    PubMed  Google Scholar 

  33. Savli H, Karadenizli A, Kolayli F, Gundes S, Ozbek U, Vahaboglu H (2003) Expression stability of six housekeeping genes: a proposal for resistance gene quantification studies of Pseudomonas aeruginosa by real-time quantitative RT-PCR. J Med Microbiol 52:403–408

    Article  PubMed  Google Scholar 

  34. Biederman J, Yee J, Cortes P (2004) Validation of internal control genes for gene expression analysis in diabetic glomerulosclerosis. Kidney Int 66:2308–2314

    Article  PubMed  Google Scholar 

  35. Ontsouka EC, Reist M, Graber H, Blum JW, Steiner A, Hirsbrunner G (2004) Expression of messenger RNA coding for 5-HT receptor, alpha and beta adrenoreceptor (subtypes) during oestrus and dioestrus in the bovine uterus. J Vet Med A Physiol Pathol Clin Med 51:385–393

    PubMed  Google Scholar 

  36. Hoerndli FJ, Toigo M, Schild A, Gotz J, Day PJ (2004) Reference genes identified in SH-SY5Y cells using custom-made gene arrays with validation by quantitative polymerase chain reaction. Anal Biochem 335:30–41

    Article  PubMed  Google Scholar 

  37. Oh J, Takahashi R, Kondo S, Mizoguchi A, Adachi E, Sasahara RM, Nishimura S, Imamura Y, Kitayama H, Alexander DB, Ide C, Horan TP, Arakawa T, Yoshida H, Nishikawa S, Itoh Y, Seiki M, Itohara S, Takahashi C, Noda M (2001) The membrane-anchored MMP inhibitor RECK is a key regulator of extracellular matrix integrity and angiogenesis. Cell 107:789–800

    Article  PubMed  Google Scholar 

  38. Jung M, Römer A, Keyszer G, Lein M, Kristiansen G, Schnorr D, Loening SA, Jung K (2003) mRNA expression of the five membrane-type matrix metalloproteinases MT1–MT5 in human prostatic cell lines and their down-regulation in human malignant prostatic tissue. Prostate 55:89–98

    Article  PubMed  Google Scholar 

  39. Stephan C, Yousef GM, Scorilas A, Jung K, Jung M, Kristiansen G, Hauptmann S, Bharaj BS, Nakamura T, Loening SA, Diamandis EP (2003) Quantitative analysis of kallikrein 15 gene expression in prostate tissue. J Urol 169:361–364

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by a grant from the Deutsche Forschungsgemeinschaft (DFG Ju 365/6-1/6-2 to K.J.) and by the Sonnenfeld-Stiftung Berlin (to K.J. and M.J.). This report includes parts of the doctoral thesis of F.O. We thank Britta Beyer for excellent technical assistance.

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Authors and Affiliations

  1. Department of Urology, Charité-Universitätsmedizin Berlin, Campus Mitte, Schumannstrasse 20/21, 10098, Berlin, Germany

    Falk Ohl, Monika Jung, Chuanliang Xu, Carsten Stephan, Anja Rabien, Stefan A. Loening & Klaus Jung

  2. Department of Urology, Changhai Hospital, Second Military Medical University, Shanghai, China

    Chuanliang Xu

  3. Institute of Pathology, Charité-Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany

    Mick Burkhardt & Glen Kristiansen

  4. Robert Koch Institute, Berlin, Germany

    Andreas Nitsche

  5. Clinic of Internal Medicine II (Oncology and Hematology), Charité-Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany

    Aleksandar Radonić

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  1. Falk Ohl
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Correspondence to Klaus Jung.

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Ohl, F., Jung, M., Xu, C. et al. Gene expression studies in prostate cancer tissue: which reference gene should be selected for normalization?. J Mol Med 83, 1014–1024 (2005). https://doi.org/10.1007/s00109-005-0703-z

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  • DOI: https://doi.org/10.1007/s00109-005-0703-z

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